184 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL"-"UCL" positions at Zintellect
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spectroradiometers. Ability to apply AI tools and machine learning for advanced image analysis, weed-crop detection, and mapping. Experience in data collection, processing, and interpretation. Strong background in
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) extracellular vesicle manufacturing and characterization high content imaging biomaterials bioreactors multiomics (proteomics/metabolomics) immunology machine learning/AI single cell profiling Point of Contact
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, Environmental Sanitation and Hygiene, and Laboratory Services. What will I be doing? Under the guidance of an epidemiologist mentor, you will be involved with and learn how to: Collect, evaluate and provide
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experience with time-series data analysis and machine learning including reinforcement learning. Applicants should be proficient in Matlab and/or Python Point of Contact ARL-RAP Eligibility Requirements
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the use of workflow tools, development environments, and resources to contribute to and implement shared bioinformatic workflows. Experiences may extend into training on Machine Learning and AI models as
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in each crop area and learn basic agronomic, data collection, and plant breeding methodologies in trials and nurseries planted at the USDA-ARS. Learning Objectives: The project assignments will provide
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for the Department of Defense, the U.S. Army and many other customers while also supporting ERDC’s research and development mission in geospatial research and engineering, military engineering, and civil works. ERDC
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of ARS National Programs 305 (Crop Production) and 304 (Crop Protection & Quarantine). The successful candidate will learn about project management by being a part of research aimed at identifying
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of genes and proteins as regulators of physiological or immunological traits. Learning Objectives: Under the guidance of the mentor, the candidate will gain experience in and learn to utilize a functional
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. market access. The approach will include metagenomics and bioinformatics to understand genetic diversity of the pathogen. Learning Objectives: During this project, the participant will be involved in